How to shift rows in python pandas dataframe

Shifting rows in a Pandas DataFrame is a common operation when working with data, especially in time series or sequential data analysis. You can shift rows up or down within a DataFrame to calculate differences, create time lags, or perform various other data transformations. In this tutorial, I will walk you through how to shift rows in a Pandas DataFrame with code examples.
Before you begin, make sure you have Python and the Pandas library installed. If you haven't already installed Pandas, you can do so using pip:
Now, let's get started with shifting rows in a Pandas DataFrame.
First, import the Pandas library in your Python script:
To demonstrate row shifting, let's create a sample DataFrame:
Here's what the DataFrame looks like:
To shift rows up within the DataFrame, you can use the shift() method. This method takes an argument periods, which specifies the number of positions to shift. A positive periods value shifts rows up, and a negative value shifts rows down.
This will shift all rows up by one position, and the first row will contain NaN values:
To shift rows down within the DataFrame, simply use a negative periods value in the shift() method: